Habitat connectivity is essential to facilitate species movement across fragmented landscapes, but hard to achieve at broad scales. The enforcement of existing land use policies could improve habitat connectivity, while providing legal support for implementation. Our goal was to evaluate how forest connectivity is affected if forests are restored according to existing riparian buffer regulations in Chile. We simulated forest restoration within 30 and 200 m of rivers in 99 large watersheds, following two sections of the forest regulation. We mapped habitat for two model forest species that have different minimum habitat sizes (15 and 30 ha), and for each we identified forest habitats and corridors using image morphology analysis. To quantify change in connectivity, we used a network graph index, the Relative Equivalent Connected Area. We found that both 30- and 200-m riparian buffers could have a positive effect on habitat connectivity. The 200-m buffers increased connectivity the most where forest cover was 20–40% (40% mean increase in connectivity index), while the 30-m buffers increased connectivity the most where forest cover was 40–60% (30% mean increase in connectivity index). The effect of riparian restoration scenarios was similar for both model species, suggesting that effective implementation of existing forest regulation could improve connectivity for fauna with a range of minimum habitat size requirements. Our findings also suggest that there is some flexibility in the buffer sizes that, if restored, would increase habitat connectivity. This flexibility could help ease the social and economic cost of implementing habitat restoration in productive lands.
File: Rojas_etal_2020_riparian_restoration_connectivity_chile_Land_urb_plan.pdf
Oceanic islands are important habitats for many endemic species. Global conservation assessments, however, are too coarse to characterize areas of high human influence or landscape connectivity at a resolution that is useful for conservation planning on most islands. Our goal was to identify landscape elements that are essential for the maintenance of structural connectivity among natural habitat patches on islands. Using the Caribbean island of Puerto Rico as a case study, our specific objectives were to: (1) develop a map of the human footprint, and (2) characterize the connectivity of patches exhibiting low human modification that structurally connect the island’s ecological network. We used the human footprint as a measure of impediments to connectivity among Puerto Rico’s natural areas using network analysis. We found that more than half of Puerto Rico’s current land surface had a low human footprint (56%), but that coastal areas were highly affected by human use (82%). Puerto Rico possesses a compact network of natural areas, with a few patches in the interior mountains critical to structural connectivity. The number of isolated patches is very high; more than 60% of the patches were 2000 m or more apart. Identifying sites that are key hubs to connectivity on islands and ensuring they remain undeveloped is one strategy to balance land use and conservation, and to facilitate the persistence of endemic species. We show here how to improve general conservation assessment methods to be more relevant for islands. There is potential to support an interconnected network of natural areas that promotes landscape connectivity in Puerto Rico among noncoastal habitats, because the human activities are concentrated along the coast whereas the interior mountain range has a relatively low human footprint.
File: Guzman-Colon-et-al_2020_Conservation-planning-for-island-nations.pdf
Marine turtles may respond to projected climatic changes by shifting their nesting range to climatically suitable areas, which may
result in either increased exposure to threats or fewer threats. Therefore, there is the need to identify whether habitat predicted to
be climatically suitable for marine turtle nesting in the future will be affected by future threats and hinder marine turtles’ ability to
adapt. We modelled the geographic distribution of climatically suitable nesting habitat for marine turtles in the USA under future
climate scenarios, identified potential range shifts by 2050, determined impacts from sea-level rise, and explored changes in
exposure to coastal development as a result of range shifts. Overall nesting ranges of marine turtle species were not predicted to
change between the current and future time periods, except for the northern nesting boundaries for loggerhead turtles. However,
declines in climatically suitable nesting grounds were predicted; loggerhead turtles will experience the highest decreases (10%) in
climatically suitable habitat followed by green (7%) and leatherback (1%) turtles. However, sea-level rise is projected to inundate
78–81% of current habitat predicted to be climatically suitable in the future, depending on species and scenario. Nevertheless,
new beaches will also form, and suitable nesting habitat could be gained, with leatherback turtles potentially experiencing the
biggest percentage gain in suitable habitat.
File: 2020_Fuentes_et_al-2020-Regional_Environmental_Change.pdf
Land degradation affects over one-third of the global land area and is projected to become even more widespread
due to climate change and land use pressures. Despite being a critical issue for climate change mitigation,
biodiversity conservation, and food security, the detection of the onset, duration, and magnitude of land de-
gradation remains challenging, as is early identification of short-term vegetation loss preceding land degrada-
tion. Here, we present a new approach for monitoring both short-term vegetation loss and decadal degradation
in grasslands using satellite data. Our approach integrates Spectral Mixture Analysis and temporal segmentation,
and analyzes dense time-series of satellite observations in three steps. First, we unmix all available satellite
observations and aggregate them into monthly composites. Second, we calculate the annual Cumulative
Endmember Fractions and examine their piecewise trends among years to determine the onset, duration, and
magnitude of short-term vegetation loss and decadal degradation. Third, we attribute a decrease in the green
vegetation fraction with a concomitant increase in either open soil, or non-photosynthetic vegetation. We tested
our method mapping short-term vegetation loss and decadal degradation in grasslands in the Caucasus Ecoregion
using the 2001–2018 time series of MODIS 8-day reflectance data. We found strong patterns of short-term
vegetation loss and decadal degradation, mostly in the eastern part of the Caucasus Ecoregion in areas of desert-
and semi-desert natural vegetation. Short-term vegetation loss episodes (3–9 years) were more common and had
greater magnitude than decadal degradation (≥10 years), especially in steppe regions. On average, 9.3% of
grassland area was subjected annually to either decadal, or short-term vegetation loss. Desiccation, i.e., the shift
from green vegetation to dry vegetation, was the most prevalent type of change pathway, with green vegetation
loss to open soil coming second. Decadal degradation and short-term vegetation loss rates were the highest in dry
areas where the potential natural vegetation is sub-shrub deserts, or halophytic, alluvial, and wet lowland
forests. Our findings support known general degradation patterns in the Caucasus Ecoregion, but provide better
understanding of ongoing processes, by detecting exact location, timing, and magnitude of changes. More
broadly, our method advances the monitoring of grasslands by detecting both decadal degradation and short-
term vegetation loss. This flexibility supports adaptive degradation monitoring, aids sustainable land manage-
ment, and provides new information for carbon stock analyses and biodiversity conservation.
File: Lewinska_etal_RSE_2020_CaucasusVegLoss.pdf
Context: Resource movements across ecosystem
boundaries are important determinants of the diversity
and abundance of organisms in the donor and recipient
ecosystem. However the effects of cross-ecosystem
movements of materials at broader spatial extents than
a typical field study are not well understood.
Objectives: We tested the hypotheses that (1) variation
in abundance of 57 forest songbird species within
four foraging guilds is explained by modeled emergent
aquatic insect biomass inputs from adjacent lakes and
streams and (2) the degree of association varies across
foraging guilds and species within guilds. We also
sought to determine the importance of emergent
aquatic insects while accounting for variation in local
forest cover and edge.
Methods: We spatially modeled the degree to which
distribution and abundance of songbirds in different
foraging guilds was explained by modeled emergent
aquatic insect biomass. We used multilevel models to
simultaneously estimate the responses of species in
four different insectivorous guilds. Bird abundance
was summarized from point counts conducted over
24 years at 317 points.
Results: Aerial insectivores were more abundant in
areas with high estimated emergent insect biomass
inputs to land (regression coefficient 0.30, P\0.05)
but the overall abundance of gleaners, bark-probers,
and ground-foragers was not explained by estimated
emergent insect abundance. The coursing aerial
insectivores had the strongest association with emergent
insects followed by willow flycatcher, olive-sided
flycatcher, and alder flycatcher.
Conclusions: Modeling cross-ecosystem movements
of materials at broad spatial extents can effectively
characterize the importance of this ecological process
for aerial insectivorous songbirds.
File: Schilke-et-al_2020_Landscape-Ecology_Modeling-a-cross-system-subsidy.pdf
Climate change is altering patterns of resource availability and this may have negative effects on insectivorous forest birds in the US upper Midwest. As invertebrate life cycle phenology shifts due to earlier spring leaf-out, nesting birds are vulnerable to phenological mismatches between food supply and demand. Areas with complex topography, and thus a variety of thermal and humidity conditions, may support a greater variety of plant and invertebrate phenological rates and stages within close proximity than are found in areas with simple topography. However, the extent and magnitude of this phenomenon is unclear, as is the degree to which topographic position may influence the ability of species to persist during extreme conditions. We examined the effects of topographic position on the
phenology of a tri-trophic forest system over two years from spring through mid-summer. We hypothesized that in cool microsites the likelihood of trophic mismatches and late season food shortages is lower than in warm microsites. At 70 sites in the Baraboo Hills, part of the Driftless Area of the US Midwest, we recorded leaf-out timing of over 700 deciduous trees, measured weekly changes in invertebrate biomass on understory foliage, and conducted bird point counts to assess avian species richness and density. In stream gorges, cooler temperatures were associated with slight but significant delays in leaf-out timing of canopy and understory deciduous trees relative to upland sites. At all sites, invertebrate biomass was distributed relatively evenly across the study period, in contrast to other temperate zone sites where phenological mismatches have been reported between birds and their invertebrate prey. Invertebrate
biomass was similar in stream gorges and uplands in both study years. Insectivorous bird species richness was greater in stream gorges than in the surrounding upland forest during both seasons and was positively related to Lepidoptera larvae biomass in the understory. Among eight abundant insectivorous bird species, density was similar in uplands and stream gorges, among four species density was higher in uplands, and density of two species was higher in stream gorges. These results suggest that insectivorous birds within this study area are unlikely to experience trophic mismatches, and that despite having cooler microclimates and higher avian species richness, stream gorges did not provide more invertebrate food resources than uplands under the climate conditions of the years in which we
sampled this tri-trophic system.
File: Persche-and-Pidgeon-2020.pdf
The positive monotonic relationship between habitat heterogeneity and species richness is a cornerstone of ecology. Recently, it was suggested that this relationship should be unimodal rather than monotonic due to a tradeoff between environmental heterogeneity and population sizes, which increases local species extinctions at high heterogeneity levels. Here, we studied the richness–heterogeneity relationship for an avian community using two different environmental variables, foliage-height diversity and cover type diversity. We analyzed the richness–heterogeneity within different habitat types (grasslands, savannas, or woodlands) and at the landscape scale. We found strong evidence that both positive and unimodal relationships exist at the landscape scale. Within habitats we found positive relationships between richness and heterogeneity in grasslands and woodlands, and unimodal relationships in savannas. We suggest that the length of the environmental heterogeneity gradient (which is affected by both spatial scale and the environmental variable being analyzed) affects the type of the richness–heterogeneity relationship. We conclude that the type of the relationship between species richness and environmental heterogeneity is non-ubiquitous, and varies both within and among habitats and environmental variables.
File: Bar-Massada-Wood-2014.pdf
Biodiversity science and conservation alike require environmental indicators to understand species richness and predict species distribution patterns. The Dynamic Habitat Indices (DHIs) are a set of three indices that summarize annual productivity measures from satellite data for biodiversity applications, and include: a) cumulative annual productivity; b) minimum annual productivity; and c) variation in annual productivity. At global scales and in temperate regions the DHIs predict species diversity patterns well, but the DHIs have not been tested in the tropics, where higher levels of productivity lead to the saturation of many remotely sensed vegetation indices. Our goal was to explain bird species richness patterns based on the DHIs in tropical areas. We related the DHIs to species richness of resident landbirds for five guilds (forest, scrub, grassland, generalist, and all resident birds) based on a) species distribution model (SDM) maps for 217 species, and b) range map for 564 species across Thailand. We also quantified the relative importance of the DHIs in multiple regression models that included two measures of topography, and two climate metrics using multiple regression, best-subsets, and hierarchical partitioning analyses. We found that the three DHIs alone explained forest bird richness best (R2adj 0.61 for both SDM- and rangemap based richness; 0.15–0.54 for the other guilds). When combining the DHIs with topography and climate, the richness of both forest birds and all resident bird species was equally well explained (R2adj 0.85 and 0.67 versus 0.81 and 0.68). Among the three DHIs, cumulative annual productivity had the greatest explanatory power for all guilds based on SDM richness maps (R2adj 0.54–0.61). The strong relationship between the DHIs and bird species richness in Thailand suggests that the DHIs capture energy availability well and are useful in biodiversity assessments and potentially bird conservation in tropical areas.
File: Suttidate_etal_RSE_TropicalBirds_DHI_2019.pdf
Biodiversity science and conservation alike require environmental indicators to understand species richness and predict species distribution patterns. The Dynamic Habitat Indices (DHIs) are a set of three indices that summarize annual productivity measures from satellite data for biodiversity applications, and include: a) cumulative annual productivity; b) minimum annual productivity; and c) variation in annual productivity. At global scales and in temperate regions the DHIs predict species diversity patterns well, but the DHIs have not been tested in the tropics, where higher levels of productivity lead to the saturation of many remotely sensed vegetation indices. Our goal was to explain bird species richness patterns based on the DHIs in tropical areas. We related the DHIs to species richness of resident landbirds for five guilds (forest, scrub, grassland, generalist, and all resident birds) based on a) species distribution model (SDM) maps for 217 species, and b) range map for 564 species across Thailand. We also quantified the relative importance of the DHIs in multiple regression models that included two measures of topography, and two climate metrics using multiple regression, best-subsets, and hierarchical partitioning analyses. We found that the three DHIs alone explained forest bird richness best (R2adj 0.61 for both SDM- and rangemap based richness; 0.15–0.54 for the other guilds). When combining the DHIs with topography and climate, the richness of both forest birds and all resident bird species was equally well explained (R2adj 0.85 and 0.67 versus 0.81 and 0.68). Among the three DHIs, cumulative annual productivity had the greatest explanatory power for all guilds based on SDM richness maps (R2adj 0.54–0.61). The strong relationship between the DHIs and bird species richness in Thailand suggests that the DHIs capture energy availability well and are useful in biodiversity assessments and potentially bird conservation in tropical areas.
